What is RPA?
RPA is the latest buzzword in the financial services industry, impacting big business decisions and driving technological research in a definitive direction.
Robotic Process Automation (RPA) enables workplace virtualization by standardizing and performing volume-driven iterative tasks. The ‘Institute for Robotic Process Automation & Artificial Intelligence’ (IRPAAI) defines RPA thus, “The application of technology that allows employees in a company to configure computer software or a ‘robot’ to capture and interpret existing applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems.”
The impact of RPA on organizational processes is analogous to that of robots in the manufacturing sector – attaining high production rates without compromising on quality. Since software applications are leveraged as part of virtualization, the ‘workforce at your disposal’ can be scaled as per requirements and there’s no risk of attrition.
The impact of RPA on organizational processes is analogous to that of robots in the manufacturing sector.
Unlike most disruptive technologies, the implementation of RPA is cost-effective as well as a timeline-optimized. It doesn’t require a complete rewiring of the existing IT landscape. A key differentiator for RPA is its user-friendly interface, which eliminates the necessity for complex system integration. Essentially, the system interacts and responds in a manner akin to a human.
How can RPA address existing challenges?
In recent years, a number of factors have emerged in the capital market ecosystem – disruptive technology, maturing expectations of digital-native customers, political uncertainty, pressure from tech-based start-ups, and an ever-evolving regulatory ecosystem. Consequently, organizations are under constant pressure to streamline costs, accelerate speed to market, ensure compliance, and stay ahead of competitors.
The combination of voluminous transactions and complex regulatory mechanisms forces enterprises to revamp operations and rethink control strategies. Robotics act as a panacea to this seemingly humungous chore, as it offers the capabilities to perform a diverse array of high-volume tasks – from fixed-asset accounting to data repository maintenance. RPA can also be leveraged to audit budgetary reports, manage invoices, and resolve vendor disputes.
Additionally, robotics enables seamless navigation of the compliance terrain. For instance, it can help scrutinize employee disclosures concerning individual accounts as well as automate the account opening process. Further, RPA expedites the examination of disclosure attestation and transfer disclosures, thereby spotting anomalies quite early.
What are the benefits of capital market process automation?
Capital markets organizations are constantly striving to extract cost benefits out of operations in order to drive profitability and improve overall growth in the long run.
Robotic automation delivers three major benefits to capital market operations – streamlined costs, enhanced control, and data analytics; without affecting the quality of service provisioning. RPA eliminates manual intervention in high-frequency tasks, leading to substantial savings by cutting-down on wages. In fact, expenses can be reduced by 50-70% for high-volume operations. Also, these tasks can be carried out during weekends or holidays, without having to hire additional resources.
As mentioned earlier, RPA supports regulatory changes and factors in cost optimized tactical solutions. Consequently, the pressure to upgrade enterprise systems and align them with new regulatory policies is significantly reduced. Due to its faster response time to market challenges, robotics encourages innovation through tactical integration. As a result, product and service innovations are developed, integrated, and incorporated without upgrades to existing systems.
Finally, as automation increases scope of enterprise data, analytics can be leveraged to generate actionable insights. Cognitive RPA, especially, derives and combines data from sources as diverse as social network, graphic information, and shared drives. Analytics can help increase profitability and overall revenue by promoting customized cross-sell and up-sell products.
What are the applications of RPA?
Robotics can facilitate the process of customer onboarding, a critical factor in customer relationship management. The seamless onboarding of customers can lead to enhanced customer satisfaction, increased retention, and improved profitability.
RPA can combine multichannel capabilities and automate workflows, thereby accelerating the onboarding process. Similarly, practices like mortgage processing, claims processing, and customer servicing can be automated to reap further benefits.
Let’s consider an example of RPA implementation – a global investment banking concern was striving to minimize costs while simultaneously reducing the time required to address issues arising from system processing. The firm deployed runbook scripting applications to help IT engineering personnel and failed. Therefore, they tried a new approach and embraced RPA. Subsequently, 80% of failed trades were resolved without human intervention, leading to 93% reduction in average resolution-and-fix time.
The next step
Any organization that employs human labor on an industrial scale for universal knowledge process work; where humans perform high-volume, highly transactional process functions, will enhance capabilities and drive significant reduction in costs and time with robotic process automation.
Today, leading organizations are already thinking beyond RPA. While some are partnering with renowned universities for the design of machine learning and AI technologies, others are investing in start-up / incubator funds for leading edge research in this domain. Companies today are offering complete automation solutions – combining all core capabilities required to digitize complex business processes – into one platform offering. Business process management (BPM), RPA, workforce orchestration, cognitive learning, and machine-learning are all combined to provide a complete robotics platform which can cut across multiple levels and offer a unified solution to today’s digital customer.